川西前陆盆地红层岩溶地貌形态特征及其地质意义

余磊; 范时杰; 梁洪; 宇天奇; 王博; 麦高飞

doi:10.11932/karst2025y006

川西前陆盆地红层岩溶地貌形态特征及其地质意义

doi: 10.11932/karst2025y006

四川水发勘测设计研究有限公司, 四川成都 610015

详细信息

作者简介:
余磊（1996－），男，助理工程师，硕士，主要从事岩溶地质、水文地质研究工作。E-mail：1279552783@qq.com

通讯作者:
范时杰（1995－），男，工程师，硕士，主要从事岩溶地质、水文地质研究工作。E-mail：905950573@qq.com。

中图分类号: P931.5
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出版历程
- 收稿日期: 2024-07-29
- 网络出版日期: 2025-09-03
- 刊出日期: 2025-06-25

Morphological characteristics and geological significance of karst landforms developed in red-bed strata of the western Sichuan foreland basin

Sichuan Water Development Investigation, Design and Research Co., Ltd., Chengdu, Sichuan 610015, China

摘要

摘要: 红层岩溶在川西前陆盆地的山地中广泛发育，查明红层岩溶的形成及演化模式，对认识红层岩溶发育具有重要意义。基于引大济岷工程野外调查数据，通过数理统计和数字地形分析的方法，量化了红层岩溶形态的参数特征，总结其空间发育规律，最后对红层岩溶演化模式进行了探讨。结果表明：岩溶泉主要分布在797~852 m、962~1 017 m和1 037~1 292 m，岩溶洼地主要分布在775~875 m、1 075~1 175 m和1 575~1 675 m，红层岩溶的发育具有高程聚集效应；洼地长轴、短轴、周长和面积均呈显著的左偏分布特征，表明在红层中发育的洼地比在碳酸盐岩中发育的规模更小，形态也更简单；K函数、核密度和面积高程积分的空间分布规律指示了红层岩溶发育严格受构造和岩性控制，研究区地貌整体处于中年阶段，受构造抬升影响，构造裂隙发育和岩体可溶性强的区域正处于地貌回春过程中。相关成果揭示了红层岩溶与碳酸盐岩岩溶在形成演化模式上有显著差异，丰富了红层岩溶研究的理论知识体系，为该地区引调水工程中可能遭遇的岩溶灾害分析提供了理论支撑。
- 红层岩溶 /
- 引大济岷 /
- 岩溶形态特征 /
- 川西前陆盆地 /
- 龙门山断裂带
Abstract: As a uniquely developed karst type in terrestrial clastic rocks, red-bed karst is widely distributed across the mountainous terrain of the western Sichuan foreland basin. Its development rules and evolution model differ significantly from those of traditional carbonate karst systems. Although academic research on traditional carbonate karst has reached a relatively advanced stage, systematic investigations into the spatial distribution characteristics, genetic mechanisms, and evolution models of red-bed karst still require in-depth exploration. In recent years, transportation tunnels and water resource allocation projects in western Sichuan have frequently encountered geological hazards such as water inrush and collapses caused by red-bed karst. These engineering-induced changes in water environment have become increasingly severe. Therefore, systematically revealing the spatial distribution patterns of red-bed karst and exploring its formation mechanisms are not only critical for deepening the scientific understanding of red-bed karst development, but also of great significance for ensuring the safety and sustainability of major engineering projects in mountainous areas of western Sichuan.This study is supported by the National and Sichuan Provincial Water Network Key Project—the Dadu–Minjiang Water Diversion Project. Based on red-bed karst morphology data collected during the engineering investigation phase in the Lianhua Mountain area (southern segment of the Longmenshan Fault Zone and western margin of the western Sichuan foreland basin), this study applied comprehensive mathematical statistics and digital terrain analysis methods. By quantifying the parameter characteristics of red-bed karst landforms, it clarified their spatial distribution patterns (including planar distribution and vertical zoning) and examined the driving factors behind the spatial differentiation of red-bed karst landforms, as well as the impact of neotectonic movements on the evolutionary stages of red-bed karst geomorphology.The results show: (1) Vertical distribution of red-bed karst landforms exhibits a significant elevation aggregation effect. Karst springs are primarily concentrated in the elevation ranges of 797 m to 852 m, 962 m to1,017 m, and 1,037 m to 1,292 m, while karst depressions are predominantly distributed at 775 m to 875 m, 1,075 m to 1,175 m, and 1,575 m to 1,675 m. Results from K-function and kernel density analyses indicate that the spatial distribution of red-bed karst landforms is significantly scale-dependent, with rock mass solubility and fracture density serving as the main controlling factors. Further analysis shows that red-bed karst depressions tend to aggregate in areas with high concentrations of soluble components in clastic rocks and well-developed groundwater runoff paths. Karst springs in red-bed strata are generally characterized by rapid recharge, short flow paths, low discharge, and a scattered distribution from multiple points. However, in regions with intense tectonic activities, large karst springs with concentrated discharge can still be developed, though their scale is significantly smaller than that of springs in carbonate karst areas under similar tectonic conditions.(2) As a typical karst feature in red beds, depressions show smaller morphological parameters (e.g., major axis, minor axis, perimeter, and area) compared to those developed in carbonate rocks, with a significantly negatively skewed distribution, indicating smaller scales in red-bed strata. The eccentricity (E) predominantly ranges from 0.75 to 1, and the compactness coefficient is mainly concentrated in the interval of 1 to 1.6, suggesting simpler edge morphology of red-bed karst depressions.(3) The spatial distribution pattern of Hypsometric Integral (HI) values further reveals that red-bed karst development is strictly controlled by tectonics and lithology, indicating that the overall geomorphic evolution of the study area has reached the mature stage. In the area where calcareous conglomerate is distributed, the drainage basin landforms exhibit significantly higher HI values than the regional average due to the highest solubility of the rock mass. This results in geomorphic evolution predominantly in the youthful stage, corresponding to active karst development. However, the low degree of actual evolution of karst landforms in these basins highlights a tectonically induced geomorphic rejuvenation process. The core of the Gaojiachang Anticline and the limbs of the Nanbaoshan Syncline, characterized by intensive structural fracture development, actively respond to tectonic uplift and are currently undergoing geomorphic rejuvenation.These results reveal significant differences in spatial distribution patterns and formation-evolution models between red-bed karst and carbonate karst. This study examines the spatial differentiation characteristics of red-bed karst and its primary developmental drivers, thereby enriching the theoretical framework of red-bed karst research. The findings provide a theoretical basis for analyzing potential red-bed karst hazards in transportation and water diversion projects in this region.
- red-bed karst /
- the Dadu-Minjiang water diversion project /
- karst morphological characteristics /
- western Sichuan foreland basin /
- the Longmenshan Fault Zone

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图 1 区域位置图

Figure 1. Location map of the study area

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图 2 区域地质简图及典型岩溶形态

Figure 2. Regional geological sketch and typical karst morphology

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图 3 岩溶洼地（a）、岩溶泉或溶洞（b）高程统计及莫兰指数

Figure 3. Elevation statistics and Moran's index of karst depression (a), karst spring or karst cave (b)

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图 4 洼地形态参数统计

注：洼地面积与数量统计柱状图（右下），纵坐标为对数刻度。

Figure 4. Statistics of morphological parameters of depressions

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图 5 洼地展布方向与节理走向统计

Figure 5. Statistics of depression distribution orientation and joint trend

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图 6 洼地偏心率与紧度系数统计

Figure 6. Statistics of depression eccentricity and compactness coefficient

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图 7 Ripley's K函数分析

注：岩溶泉（或溶洞）K函数（左），红层岩溶洼地K函数（右）。

Figure 7. Analysis of Ripley 's K function

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图 8 核密度分布图

Figure 8. Kernel density distribution map

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图 9 HI空间分布图

Figure 9. HI spatial distribution map

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表 1 红层岩溶形态的量化参数及意义

Table 1. Quantitative parameters and significance of red-bed karst morphology

指标类型	指标名称	量化方式	形态参数的意义
高程分布参数	泉点、溶洞高程	中绘i80 GNSS接收机测定	泉点、溶洞出露点的海拔高程
	洼地高程	ArcGIS平台Extract Multi Values To Points工具	洼地最低点海拔高程
	全局莫兰指数（IG）	ArcGIS平台Spatial Autocorrelation工具	度量地理对象的空间自相关程度和聚散特征。IG∈（0,1]，空间聚集形态；IG=0,随机分布；IG∈[−1,0),空间离散形态；绝对值越大，自相关性越显著
洼地形态参数	洼地长轴、短轴	ArcGIS平台Minimum Bounding Geometry工具	长轴（L）：洼地外接最小矩形的长边短轴（W）：洼地外接最小矩形的短边
	洼地展布方向	ArcGIS平台Calculate Polygon Main Angle工具	洼地长轴的走向，反映洼地发育趋势方向
	偏心率（E）	公式$ \boldsymbol{E}=\sqrt{1-\dfrac{{(\boldsymbol{W}/2)}^{2}}{{(\boldsymbol{L}/2)}^{2}}} $计算	反映洼地多边形的标准程度。E=0，洼地外接多边形为正多边形，E∈(0,1)，数值越大，外接多边形越狭长^[32]
	面积（A）	ArcGIS平台直接计算	洼地最大封闭等高线的投影面积和长度
	周长（S）	ArcGIS平台直接计算	洼地最大封闭等高线的投影面积和长度
	紧度系数（T）	由公式$ \boldsymbol{T}=\dfrac{0.028\;2\boldsymbol{S}}{\sqrt{\boldsymbol{A}}} $计算	洼地实际周长与相同面积标准圆周长之比。T∈（1,∞]，T值越大，洼地外接多边形边缘越复杂^[40]
红层岩溶形态空间分布指标	Ripley's K函数	ArcGIS平台Multi-Distance Spatial Cluster Analysis 工具	反映红层岩溶形态分布状态。K观测值＞HiConfEnvz值（Monte Carlo空间模式检验上限），具备显著统计性，反之为不具备^[33]
	核密度	ArcGIS平台Kernel Density工具	点状数据空间分布状态，以描述红层岩溶形态的空间分布特征
	面积高程积分值（HI）	ArcGIS平台实现	以二维曲线或数值反映地表物质相对侵蚀量，可用以量化流域发育阶段，$ {{\rm{HI}}}=\dfrac{({流}{域}{平}{均}{高}{程}-{流}{域}{最}{小}{高}{程})}{({流}{域}{最}{大}{高}{程}-{流}{域}{最}{小}{高}{程})} $。

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